Noninvasive evaluation of cerebral glioma grade by using multivoxel 3D proton MR spectroscopy

Magnetic Resonance Spectroscopy of Intra-axial Gliomas With Histopathological Correlation in a Tertiary Care Center of Eastern Nepal

Background and objective Magnetic resonance spectroscopy (MRS) is a magnetic resonance imaging technique used to identify in vivo metabolites non-invasively within the tissue of interest. It plays an important role in diagnosing brain lesions, particularly tumors and infections. There are certain metabolites whose levels are increased or decreased in brain tumors, the ratios of which can also be used to grade the tumors as high- or low-grade. This study aimed to assess the spectrum of different metabolites in intraaxial gliomas using magnetic resonance spectroscopy and to assess the usefulness of their ratios for grading gliomas into high-grade and low-grade. Methods This descriptive cross-sectional study was performed in the radiology department of Nobel Medical College and Teaching Hospital, Biratnagar, Nepal over one year (September 2019 to September 2020). Thirty-five patients diagnosed as having intra-axial tumors were enrolled. After taking informed consent the examination findings were recorded in structured proforma. Siemens' 3 Tesla open magnet MAGNETOM Skyra (Siemens Healthineers AG, Munich, Germany) MR scanner was used to evaluate each patient. Data was analyzed using the software Statistical Package for Social Sciences (SPSS), version 26.0 (IBM Corp., Armonk, NY). Results Out of 35 patients scanned, 18 had high-grade glioma and 17 had low-grade glioma. High-grade glioma had a choline/creatine (Cho/Cr) ratio of 2.44 ± 0.78 and a choline/N-acetyl-aspartate (Cho/NAA) ratio of 2.05 ± 0.84. Low-grade glioma had a Cho/Cr ratio of 1.48 ± 0.50 and a Cho/NAA ratio of 1.41 ± 0.19. Fourteen out of eighteen high-grade gliomas had raised lipid/lactate peaks. The sensitivity, specificity, positive and negative predictive values (PPV and NPV), and accuracy for diagnosing high-grade glioma with a Cho/Cr ratio cut-off of 1.5 was 83.3 %, 82.4%, 83.3%,82.4 %, and 82.85% respectively. Conclusion MRS metabolite ratios can be used to diagnose and grade gliomas. Cho/Cr, Cho/NAA, and the presence or absence of lipid/lactate peak can significantly improve the sensitivity, specificity, predictive values, and accuracy of preoperative glioma grading when used in conjunction with conventional MRI.

DHRS2 inhibits cell growth and metastasis in ovarian cancer by downregulation of CHKα to disrupt choline metabolism

The short-chain dehydrogenase/reductase (SDR) superfamily has essential roles in lipid metabolism and redox sensing. In recent years, accumulating evidence highlights the emerging association between SDR family enzymes and cancer. Dehydrogenase/reductase member 2(DHRS2) belongs to the NADH/NADPH-dependent SDR family, and extensively participates in the regulation of the proliferation, migration, and chemoresistance of cancer cells. However, the underlying mechanism has not been well defined. In the present study, we have demonstrated that DHRS2 inhibits the growth and metastasis of ovarian cancer (OC) cells in vitro and in vivo. Mechanistically, the combination of transcriptome and metabolome reveals an interruption of choline metabolism by DHRS2. DHRS2 post-transcriptionally downregulates choline kinase α (CHKα) to inhibit AKT signaling activation and reduce phosphorylcholine (PC)/glycerophosphorylcholine (GPC) ratio, impeding choline metabolism reprogramming in OC. These actions mainly account for the tumor-suppressive role of DHRS2 in OC. Overall, our findings establish the mechanistic connection among metabolic enzymes, metabolites, and the malignant phenotype of cancer cells. This could result in further development of novel pharmacological tools against OC by the induction of DHRS2 to disrupt the choline metabolic pathway.

1H-MR spectroscopy in grading of cerebral glioma: A new view point, MRS image quality assessment

Background

Noninvasive preoperative prediction of histological grading is essential for clinical management of cerebral glioma.

Purpose

This study aimed to investigate the association between the image quality assessment of 1H magnetic resonance spectroscopy and accurate grading of glioma.

Materials and Methods

98 glioma patients confirmed by pathology were retrospectively recruited in this single-center study. All patients underwent 1H-MRS examination at 3.0T before surgery. According to WHO standards, all cases were divided into two groups: low-grade glioma (grade I and II, 48 cases) and high-grade glioma (grades III and IV, 50 cases). The metabolite ratios in both grades were calculated before and after image quality assessment. The area under the receiver operating characteristic (ROC) curve was used to evaluate the capacity of each ratio in glioma grading.

Results

The Cho/Cr, Cho/NAA and NAA/Cr metabolite ratios had certain differences in each glioma group before and after MRS image quality assessment. In the low-grade glioma group, there was a dramatic difference in the Cho/Cr ratio before and after image quality assessment (p = 0.011). After MRS image quality assessment, the accuracy of glioma grading was significantly improved. The Cho/Cr ratio with 83.3% sensitivity and 93.7% specificity is the best index of glioma grading, with the optimal cutoff value of the Cho/Cr ratio being 3.72.

Conclusion

The image quality of MRS does affect the metabolite ratios and the results of glioma grading. MRS image quality assessment can observably improve the accuracy rate of glioma grading. The Cho/Cr ratio has the best diagnostic performance in differentiating high-grade from low-grade glioma.

Diagnostic Accuracy of Magnetic Resonance Spectroscopy in Predicting the Grade of Glioma Keeping Histopathology as the Gold Standard

Background

Gliomas are the most prevalent intrinsic tumors of the central nervous system and are categorized from grade I to grade IV. Magnetic resonance imaging (MRI) provides exact diagnosis, prognosis, and assessment of tumor response to current chemotherapy/immunotherapy and radiation therapy. With histopathology serving as the gold standard, we aimed to assess the diagnostic accuracy of magnetic resonance spectroscopy (MRS) in predicting glioma grade.

Methodology

This cross-sectional study was conducted in the Department of Radiology, KRL Hospital, Islamabad, from December 15, 2019, to September 30, 2021. After providing written consent, 80 patients with untreated gliomas were included in this study. The voxel of interest was identified using MRI brain conventional contrast-enhanced sequences to assess the grade of the gliomas and link it to the histology report. Following this identification, tissue metabolites were calculated using MRS.

Results

The patients’ age ranged from 13 to 80 years, with a mean age of 49.5 years. Male patients comprised 57.5% of the total study population, while female patients comprised 42.5%. Overall, 23.75% of patients had low-grade tumors, while 76.25% had high-grade tumors. Low-grade tumors had a choline (Cho)/creatine (Cr) metabolite ratio of 1.7421, whereas high-grade tumors had an average Cho/Cr metabolite ratio of 2.5575. N-acetyl aspartate (NAA)/Cr ratio was 1.6368 in low grade and 0.6734 in high-grade tumors. Sensitivity of 77% and specificity of 84.2% were noted, with 78.75% diagnostic accuracy for the Cho/Cr ratio.

Conclusions

Multivoxel MRS has been shown to reliably predict the grade of gliomas despite its non-invasive nature and lack of procedural challenges. When used together Cho/Cr and NAA/Cr ratios and histopathology can accurately determine tumor grade and can be used as a supplementary non-invasive technique.

Urine-Based Metabolomics and Machine Learning Reveals Metabolites Associated with Renal Cell Carcinoma Stage

Urine metabolomics profiling has potential for non-invasive RCC staging, in addition to providing metabolic insights into disease progression. In this study, we utilized liquid chromatography-mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and machine learning (ML) for the discovery of urine metabolites associated with RCC progression. Two machine learning questions were posed in the study: Binary classification into early RCC (stage I and II) and advanced RCC stages (stage III and IV), and RCC tumor size estimation through regression analysis. A total of 82 RCC patients with known tumor size and metabolomic measurements were used for the regression task, and 70 RCC patients with complete tumor-nodes-metastasis (TNM) staging information were used for the classification tasks under ten-fold cross-validation conditions. A voting ensemble regression model consisting of elastic net, ridge, and support vector regressor predicted RCC tumor size with a R² value of 0.58. A voting classifier model consisting of random forest, support vector machines, logistic regression, and adaptive boosting yielded an AUC of 0.96 and an accuracy of 87%. Some identified metabolites associated with renal cell carcinoma progression included 4-guanidinobutanoic acid, 7-aminomethyl-7-carbaguanine, 3-hydroxyanthranilic acid, lysyl-glycine, glycine, citrate, and pyruvate. Overall, we identified a urine metabolic phenotype associated with renal cell carcinoma stage, exploring the promise of a urine-based metabolomic assay for staging this disease.

The combined role of MR spectroscopy and perfusion imaging in preoperative differentiation between high- and low-grade gliomas

Background

Brain tumors are an important health problem. The preoperative classification of gliomas by non-invasive techniques is a significant problem. Relative cerebral blood volume and spectroscopy have the ability to sample the entire lesion non-invasively. The present study aims to evaluate the combined role of dynamic susceptibility perfusion and spectroscopy in the classification of primary brain tumors. The combination of both provides overall diagnostic accuracy (100%). Relative cerebral blood volume in peritumoral region plays an important additional role in this regard.

Results

On the basis of histopathology, among 50 patients with brain tumors, high-grade gliomas accounted for 58%, while low-grade gliomas accounted for 42%. The relative cerebral blood volume in the tumor had the best sensitivity, specificity, and accuracy of 96.8%, 95.3%, and 96, respectively. The use of relative cerebral blood volume and choline/N-acetyl Aspartate increased diagnostic accuracy by 100%.

Conclusion

The combination of magnetic resonance spectroscopy and perfusion can increase sensitivity and positive predictive value to define the degree of glioma.

Analysis of metabolic abnormalities in high-grade glioma using MRSI and convex NMF

Clinical use of MRSI is limited by the level of experience required to properly translate MRSI examinations into relevant clinical information. To solve this, several methods have been proposed to automatically recognize a predefined set of reference metabolic patterns. Given the variety of metabolic patterns seen in glioma patients, the decision on the optimal number of patterns that need to be used to describe the data is not trivial. In this paper, we propose a novel framework to (1) separate healthy from abnormal metabolic patterns and (2) retrieve an optimal number of reference patterns describing the most important types of abnormality. Using 41 MRSI examinations (1.5 T, PRESS, T_E 135 ms) from 22 glioma patients, four different patterns describing different types of abnormality were detected: edema, healthy without Glx, active tumor and necrosis. The identified patterns were then evaluated on 17 MRSI examinations from nine different glioma patients. The results were compared against BraTumIA, an automatic segmentation method trained to identify different tumor compartments on structural MRI data. Finally, the ability to predict future contrast enhancement using the proposed approach was also evaluated.

Lack of choline elevation on proton magnetic resonance spectroscopy in grade I-III gliomas

Elevated levels of choline are generally emphasized as marker of increased cellularity and cell membrane turnover in gliomas. In this study, we investigated the incidence rate of lack of choline/creatine and choline/water elevation in a population of grade I-III gliomas. A cohort of 41 patients with histopathologically confirmed gliomas underwent multi-voxel proton magnetic resonance spectroscopy on a 3 T magnetic resonance system prior to treatment. Peak areas for choline and myoinositol were measured from all voxels that exhibited hyperintensity on fluid-attenuated inversion recovery images and were normalized to creatine and unsuppressed water from each voxel. The average metabolite/creatine and metabolite/water ratios from these voxels were then computed. Similarly, average metabolite ratios were computed from normal brain parenchyma. Gliomas were considered for lack of choline elevation when choline/creatine and choline/water ratios from neoplastic regions were less than those from normal brain parenchyma regions. Six of 41 (14.6%) grade I-III gliomas showed lack of elevation for choline/creatine and choline/water ratios compared to normal brain parenchyma. Four of these six gliomas also demonstrated elevated levels of myoinositol/creatine ratio. All other gliomas (n = 35) had elevated choline levels from neoplastic regions relative to normal parenchyma. The sensitivity of choline/creatine or choline/water in determining a grade I-III glioma was 85.4%. These findings suggest that a lack of choline/creatine or choline/water elevation may be seen in some gliomas and low choline levels should not prevent us from considering the possibility of a grade I-III glioma.

Preoperative grading of intracranial meningioma by magnetic resonance spectroscopy (1H-MRS)

Although proton magnetic resonance spectroscopy (¹H-MRS) is a common method for the evaluation of intracranial meningiomas, controversy exists regarding which parameter of ¹H-MRS best predicts the histopathological grade of an intracranial meningioma. In this study, we evaluated the results of pre-operative ¹H-MRS to identify predictive factors for high-grade intracranial meningioma. Thirteen patients with World Health Organization (WHO) grade II-III meningioma (confirmed by pathology) were defined as high-grade; twenty-two patients with WHO grade I meningioma were defined as low-grade. All patients were evaluated by ¹H-MRS before surgery. The relationships between the ratios of metabolites (N-acetylaspartate [NAA], creatine [Cr], and choline [Cho]) and the diagnosis of high-grade meningioma were analyzed. According to Mann-Whitney U test analysis, the Cho/NAA ratio in cases of high-grade meningioma was significantly higher than in cases of low-grade meningioma (6.34 ± 7.90 vs. 1.58 ± 0.77, p<0.05); however, there were no differences in age, Cho/Cr, or NAA/Cr. According to conditional inference tree analysis, the optimal cut-off point for the Cho/NAA ration between high-grade and low-grade meningioma was 2.409 (sensitivity = 61.54%; specificity = 86.36%). This analysis of pre-operative ¹H-MRS metabolite ratio demonstrated that the Cho/NAA ratio may provide a simple and practical predictive value for high-grade intracranial meningiomas, and may aid neurosurgeons in efforts to design an appropriate surgical plan and treatment strategy before surgery.

The Role of Advanced Brain Tumor Imaging in the Care of Patients with Central Nervous System Malignancies

OPINION STATEMENT

T1-weighted post-contrast and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) constitute the gold standard for diagnosis and response assessment in neuro-oncologic patients but are limited in their ability to accurately reflect tumor biology and metabolism, particularly over the course of a patient's treatment. Advanced MR imaging methods are sensitized to different biophysical processes in tissue, including blood perfusion, tumor metabolism, and chemical composition of tissue, and provide more specific information on tissue physiology than standard MRI. This review provides an overview of the most common and emerging advanced imaging modalities in the field of brain tumor imaging and their applications in the care of neuro-oncologic patients.

Role of Multivoxel Intermediate TE 2D CSI MR Spectroscopy and 2D Echoplanar Diffusion Imaging in Grading of Primary Glial Brain Tumours

INTRODUCTION

Preoperative tumour grading is imperative owing to difference in invasive, aggressive tendencies of different grades of glial tumours implying varied prognosis, therapeutic options. Histopathological examination has inherent sampling errors. Magnetic Resonance Spectroscopy (MRS) and Diffusion Weighted Imaging (DWI) can provide non invasive information about internal mileu hence, aiding in tumour grading by adding to information provided by conventional MRI sequences.

AIM

To evaluate the role of multivoxel intermediate TE 2D CSI MRS and 2D echoplanar diffusion imaging in grading of primary glial brain tumours.

MATERIAL AND METHODS

A prospective study was conducted in Department of Radiology, Teerthanker Mahaveer Medical College and Research Centre, Uttar Pradesh, India, from April 2015 to August 2016 after obtaining necessary approvals from Institutional Ethical Committee and written informed consent from all participants on histopathological proven cases of glial brain tumours that underwent multivoxel MRS using intermediate TE 2D chemical shift imaging and DWI using 2D echoplanar imaging. Tumour grade calculated on MRI using MRS and DWI was compared with histopathological grading. Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity, specificity and accuracy were calculated for each parameter and statistical significance was evaluated using two tailed Pearson test.

RESULTS

Choline: N Acetyl aspartate (Cho: NAA) and Choline: creatinine (Cho: Cr) ratios from MRS as well as Apparent Diffusion Coffecient (ADC) values from DWI were significantly higher with increasing severity of tumour grade. Accuracy of 58.6% was obtained with DWI while it was 83% with MRS. MRS and DWI used together provided 88.4% accuracy. All parameters evaluated showed statistical significance.

CONCLUSION

Both DWI as well as MRS were found to have statistically significant roles in grading of glial brain tumours. MRS was found to be more useful than DWI.

Diagnostic performance between contrast enhancement, proton MR spectroscopy, and amide proton transfer imaging in patients with brain tumors

PURPOSE

To explore the relationship among parameters of magnetic resonance spectroscopy (MRS) and amide proton transfer (APT) imaging, and to assess the diagnostic performance of MRS and APT imaging for grading brain tumors in comparison with contrast enhancement of conventional MRI for preoperative grading in patients with brain tumor.

MATERIALS AND METHODS

Institutional Review Board approval and written informed consent were obtained. Forty-one patients with suspected brain tumors were enrolled in the study. Single-voxel MRS and 2D APT imaging of the same slice level were conducted using a 3T MRI scanner. Positive or negative contrast enhancement on T₁ -weighted images was assessed by two neuroradiologists. Correlations among metabolite concentrations, metabolite ratios, and calculated histogram parameters, including mean APT (APT_mean ) and the 90th percentile of APT (APT₉₀ ) were assessed using Spearman's correlation coefficient. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis for contrast enhancement and MRS and APT imaging. Values of P < 0.05 were considered statistically significant.

RESULTS

Positive correlations with statistical significance were found between total concentration of choline (Cho) and APT₉₀ (r = 0.49), and between Cho/creatine (Cr) and APT_mean (r = 0.65) as well as APT₉₀ (r = 0.49). A negative correlation with statistical significance was observed between NAA/Cr and APT_mean (r = -0.52). According to ROC curves, Cho/Cr, APT_mean , APT₉₀ , demonstrated higher area under the curve (AUC) values than that of contrast enhancement in grading gliomas.

CONCLUSION

Significant correlations were observed between metabolite concentrations and ratios on MRS and APT values. MRS and APT imaging showed comparable diagnostic capability for grading brain tumors, suggesting that both MRS and APT imaging offer potential for quantitatively assessing similar biological characteristics in brain tumors on noncontrast MRI.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:732-739.

The action of β-hydroxybutyrate on the growth, metabolism and global histone H3 acetylation of spontaneous mouse mammary tumours: evidence of a β-hydroxybutyrate paradox

BACKGROUND

Ketone bodies have both metabolic and epigenetic roles in cancer. In several studies, they showed an anti-cancer effect via inhibition of histone deacetylases; however, other studies observed faster tumour growth. The related molecule butyrate also inhibits growth of some cancer cells and accelerates it in others. This "butyrate paradox" is thought to be due to butyrate mediating histone acetylation and thus inhibiting cell proliferation in cancers that preferentially utilise glucose (the Warburg effect); whereas in cells that oxidise butyrate as a fuel, it fails to reach inhibitory concentrations and can stimulate growth.

METHODS

We treated transgenic mice bearing spontaneous MMTV-NEU-NT mammary tumours with the ketone body β-hydroxybutyrate (β-OHB) and monitored tumour growth, metabolite concentrations and histone acetylation. In a cell line derived from these tumours, we also measured uptake of β-OHB and glucose, and lactate production, in the absence and presence of β-OHB.

RESULTS

β-OHB administration accelerated growth of MMTV-NEU-NT tumours, and their metabolic profile showed significant increases in ATP, glutamine, serine and choline-related metabolites. The β-OHB concentration within the treated tumours, 0.46 ± 0.05 μmol/g, had no effect on histone acetylation as shown by western blots. Cultured tumour cells incubated with 0.5 mM β-OHB showed β-OHB uptake that would be equivalent to 54% of glycolytic ATP phosphorylation and no significant change in glucose consumption or lactate production.

CONCLUSIONS

These results suggest that a β-OHB paradox may occur in these mammary tumours in a manner analogous to the butyrate paradox. At low β-OHB concentrations (<1 mM, as observed in our tumour model post-treatment), and in the absence of a Warburg effect, β-OHB is consumed and thus acts as an oxidative energy source and not as an epigenetic factor. This would explain the increase in tumour growth after treatment, the metabolic profiles and the absence of an effect on histone H3 acetylation.

Multivoxel magnetic resonance spectroscopy identifies enriched foci of cancer stem-like cells in high-grade gliomas

OBJECTIVE

This study investigated the correlation between choline/creatine (Cho/Cr) ratios determined by multivoxel proton magnetic resonance spectroscopy (¹H-MRS) and the distribution of cancer stem-like cells (CSLCs) in high-grade gliomas.

PATIENTS AND METHODS

Sixteen patients with high-grade gliomas were recruited and underwent ¹H-MRS examination before surgery to identify distinct tumor regions with variable Cho/Cr ratios. Using intraoperative neuronavigation, tumor tissues were accurately sampled from regions with high and low Cho/Cr ratios within each tumor. The distribution of CSLCs in samples from glioma tissue regions with different Cho/Cr ratios was quantified by neurosphere culture, immunohistochemistry, and Western blot.

RESULTS

The mean neurosphere formation rate in tissues with high Cho/Cr ratios was significantly increased compared with that in low Cho/Cr ratio tissues (13.94±5.94 per 100 cells vs 8.04±3.99 per 100 cells, P<0.001). Immunohistochemistry indicated that tissues with high Cho/Cr ratios had elevated expression of CD133, nestin, and CD15, relative to low Cho/Cr ratio tissue samples (23.6%±3.8% vs 18.3%±3.3%, 25.2%±4.5% vs 19.8%±2.8%, 24.5%±3.8% vs 17.8%±2.2%, respectively; all P<0.001). Western blot demonstrated that relative CD133 and nestin protein expression in high Cho/Cr ratio regions was significantly higher than that in low Cho/Cr ratio tissue samples (0.50±0.17 vs 0.30±0.08, 0.45±0.13 vs 0.27±0.07, respectively; both P<0.001). The protein expression levels of CD133 and nestin were highly correlated with Cho/Cr ratios (r=0.897 and r=0.861, respectively).

CONCLUSION

Cho/Cr ratios correlate with the distribution of CSLCs in high-grade gliomas, and this may assist in identifying foci enriched with CSLCs and thus improve the management of high-grade gliomas.

Differential diagnosis of human lung tumors using surface desorption atmospheric pressure chemical ionization imaging mass spectrometry

Differential diagnosis of human lung cancer in untreated tissue is achieved by DAPCI-MSI combined with multivariate statistical analysis.

Clinical Imaging of Tumor Metabolism with ¹H Magnetic Resonance Spectroscopy

Magnetic resonance spectroscopy (MRS) is a noninvasive functional technique to evaluate the biochemical behavior of human tissues. This property has been widely used in assessment and therapy monitoring of brain tumors. MRS studies can be implemented outside the brain, with successful and promising results in the evaluation of prostate and breast cancer, although still with limited reproducibility. As a result of technical improvements, malignancies of the musculoskeletal system and abdominopelvic organs can benefit from the molecular information that MRS provides. The technical challenges and main applications in oncology of (1)H MRS in a clinical setting are the focus of this review.

Noninvasive evaluation of radiation-enhanced glioma cells invasiveness by ultra-high-field (1)H-MRS in vitro

INTRODUCTION

Glioma is the most common type of the primary CNS tumor. Radiotherapy is an important treatment measure after surgery. However, its highly invasive character is the main reason of postoperative recurrence. The aim of the study was to probe the correlation between the invasion ability and the metabolite characteristics of glioma cells at the cellular level after irradiation by using 14.7T high-resolution nuclear proton magnetic resonance spectroscopy ((1)H-MRS).

METHODS

To determine the matrix metalloproteinase-2 (MMP-2) activity and metabolite ratios of glioma cells after irradiation with different doses of X-rays, U87 and C6 glioma cells were exposed to X-ray irradiation of 0, 1, 5, 10, and 15Gy. After 20h, the perchloric acid (PCA) extraction method was used to evaluate water-soluble metabolites [choline (Cho), creatine (Cr), and N-acetylaspartate (NAA)], and (1)H-MRS patterns and changes in metabolite ratios were observed in vitro by 14.7T high resolution (1)H-MRS. Matrigel invasion assays and gelatin zymography were performed to test the invasion ability of U87 and C6 glioma cells.

RESULTS

Good MR spectra were obtained from PCA method extracts of U87 and C6 glioma cells. Both radiation-induced MMP-2 activity and the Cho/Cr and Cho/NAA ratios increased after irradiation, and their increase occurred in a dose-dependent manner. The MMP-2 activity and the Cho/Cr and Cho/NAA ratios of glioma cells increased after irradiation up to 10Gy and decreased thereafter. In particular, the Cho/NAA ratio of U87 cells increased from 3.55±0.06 (0Gy) to 9.13±0.30 (10Gy) and then declined to 5.94±0.15 (15Gy). Furthermore, the invasion ability of glioma cells had a strong positive correlation with the Cho/Cr and Cho/NAA ratios. Both the Cho/Cr ratio and the Cho/NAA ratio of U87 glioma cells were highly positively correlated with the number of invading cells in the Matrigel invasion assay. The Pearson's correlation coefficient (r) values of U87 cells were 0.89 (Cho/Cr ratio versus invasion ability) and 0.91 (Cho/NAA ratio versus invasion ability) (P<0.01). C6 cells exhibited similar changes to those of U87 cells.

CONCLUSIONS

In vitro high-resolution (1)H-MRS is useful for detecting glioma invasiveness at the cellular level.

Neuroimaging

Imaging is integral to the management of patients with brain tumors. Conventional structural imaging provides exquisite anatomic detail but remains limited in the evaluation of molecular characteristics of intracranial neoplasms. Quantitative and physiologic biomarkers derived from advanced imaging techniques have been increasingly utilized as problem-solving tools to identify glioma grade and assess response to therapy. This chapter provides a comprehensive overview of the imaging strategies used in the clinical assessment of patients with gliomas and describes how novel imaging biomarkers have the potential to improve patient management.

The role of imaging in the management of adults with diffuse low grade glioma: A systematic review and evidence-based clinical practice guideline

QUESTION

What is the optimal imaging technique to be used in the diagnosis of a suspected low grade glioma, specifically: which anatomic imaging sequences are critical for most accurately identifying or diagnosing a low grade glioma (LGG) and do non-anatomic imaging methods and/or sequences add to the diagnostic specificity of suspected low grade gliomas?

TARGET POPULATION

These recommendations apply to adults with a newly diagnosed lesion with a suspected or histopathologically proven LGG.

RECOMMENDATION

LEVEL II

In patients with a suspected brain tumor, the minimum magnetic resonance imaging (MRI) exam should be an anatomic exam with both T2 weighted and pre- and post-gadolinium contrast enhanced T1 weighted imaging. CRITICAL IMAGING FOR THE IDENTIFICATION AND DIAGNOSIS OF LOW GRADE GLIOMA:

LEVEL II

In patients with a suspected brain tumor, anatomic imaging sequences should include T1 and T2 weighted and Fluid Attenuation Inversion Recovery (FLAIR) MR sequences and will include T1 weighted imaging after the administration of gadolinium based contrast. Computed tomography (CT) can provide additional information regarding calcification or hemorrhage, which may narrow the differential diagnosis. At a minimum, these anatomic sequences can help identify a lesion as well as its location, and potential for surgical intervention. IMPROVEMENT OF DIAGNOSTIC SPECIFICITY WITH THE ADDITION OF NON-ANATOMIC (PHYSIOLOGIC AND ADVANCED IMAGING) TO ANATOMIC IMAGING:

LEVEL II

Class II evidence from multiple studies and a significant number of Class III series support the addition of diffusion and perfusion weighted MR imaging in the assessment of suspected LGGs, for the purposes of discriminating the potential for tumor subtypes and identification of suspicion of higher grade diagnoses.

LEVEL III

Multiple series offer Class III evidence to support the potential for magnetic resonance spectroscopy (MRS) and nuclear medicine methods including positron emission tomography and single-photon emission computed tomography imaging to offer additional diagnostic specificity although these are less well defined and their roles in clinical practice are still being defined.

QUESTION

Which imaging sequences or parameters best predict the biological behavior or prognosis for patients with LGG?

TARGET POPULATION

These recommendations apply to adults with a newly diagnosed lesion with a suspected or histopathologically proven LGG.

RECOMMENDATION

Anatomic and advanced imaging methods and prognostic stratification

LEVEL III

Multiple series suggest a role for anatomic and advanced sequences to suggest prognostic stratification among low grade gliomas. Perfusion weighted imaging, particularly when obtained as a part of diagnostic evaluation (as recommended above) can play a role in consideration of prognosis. Other imaging sequences remain investigational in terms of their role in consideration of tumor prognosis as there is insufficient evidence to support more formal recommendations as to their use at this time.

QUESTION

What is the optimal imaging technique to be used in the follow-up of a suspected (or biopsy proven) LGG?

TARGET POPULATION

This recommendation applies to adults with a newly diagnosed low grade glioma.

RECOMMENDATIONS

LEVEL II

In patients with a diagnosis of LGG, anatomic imaging sequences should include T2/FLAIR MR sequences and T1 weighted imaging before and after the administration of gadolinium based contrast. Serial imaging should be performed to identify new areas of contrast enhancement or significant change in tumor size, which may signify transformation to a higher grade.

LEVEL III

Advanced imaging utility may depend on tumor subtype. Multicenter clinical trials with larger cohorts are needed. For astrocytic tumors, baseline and longitudinal elevations in tumor perfusion as assessed by dynamic susceptibility contrast perfusion MRI are associated with shorter time to tumor progression, but can be difficult to standardize in clinical practice. For oligodendrogliomas and mixed gliomas, MRS may be helpful for identification of progression.

The diagnostic performance of magnetic resonance spectroscopy in differentiating high-from low-grade gliomas: A systematic review and meta-analysis

OBJECTIVE

Magnetic resonance spectroscopy (MRS) is a powerful tool for preoperative grading of gliomas. We performed a meta-analysis to evaluate the diagnostic performance of MRS in differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs).

METHODS

PubMed and Embase databases were systematically searched for relevant studies of glioma grading assessed by MRS through 27 March 2015. Based on the data from eligible studies, pooled sensitivity, specificity, diagnostic odds ratio and areas under summary receiver operating characteristic curve (SROC) of different metabolite ratios were obtained.

RESULTS

Thirty articles comprising a total sample size of 1228 patients were included in our meta-analysis. Quantitative synthesis of studies showed that the pooled sensitivity/specificity of Cho/Cr, Cho/NAA and NAA/Cr ratios was 0.75/0.60, 0.80/0.76 and 0.71/0.70, respectively. The area under the curve (AUC) of the SROC was 0.83, 0.87 and 0.78, respectively.

CONCLUSIONS

MRS demonstrated moderate diagnostic performance in distinguishing HGGs from LGGs using tumoural metabolite ratios including Cho/Cr, Cho/NAA and NAA/Cr. Although there was no significant difference in AUC between Cho/Cr and Cho/NAA groups, Cho/NAA ratio showed higher sensitivity and specificity than Cho/Cr ratio and NAA/Cr ratio. We suggest that MRS should combine other advanced imaging techniques to improve diagnostic accuracy in differentiating HGGs from LGGs.

KEY POINTS

• MRS has moderate diagnostic performance in distinguishing HGGs from LGGs. • There is no significant difference in AUC between Cho/Cr and Cho/NAA ratios. • Cho/NAA ratio is superior to NAA/Cr ratio. • Cho/NAA ratio shows higher sensitivity and specificity than Cho/Cr and NAA/Cr ratios. • MRS should combine other advanced imaging techniques to improve diagnostic accuracy.

Convex-Envelope Based Automated Quantitative Approach to Multi-Voxel 1H-MRS Applied to Brain Tumor Analysis

Background

Magnetic Resonance Spectroscopy (MRS) can measure in vivo brain tissue metabolism that exhibits unique biochemical characteristics in brain tumors. For clinical application, an efficient and versatile quantification method of MRS would be an important tool for medical research, particularly for exploring the scientific problem of tumor monitoring. The objective of our study is to propose an automated MRS quantitative approach and assess the feasibility of this approach for glioma grading, prognosis and boundary detection.

Methods

An automated quantitative approach based on a convex envelope (AQoCE) is proposed in this paper, including preprocessing, convex-envelope based baseline fitting, bias correction, sectional baseline removal, and peak detection, in a total of 5 steps. Some metabolic ratios acquired by this quantification are selected for statistical analysis. An independent sample t-test and the Kruskal-Wallis test are used for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and for detecting the tumor, peritumoral and contralateral areas, respectively. Seventy-eight cases of pre-operative brain gliomas with pathological reports are included in this study.

Results

Cho/NAA, Cho/Cr and Lip-Lac/Cr (LL/Cr) calculated by AQoCE in the tumor area differ significantly between LGG and HGG, with p≤0.005. Using logistic regression combining Cho/NAA, Cho/Cr and LL/Cr to generate a ROC curve, AQoCE achieves a sensitivity of 92.9%, a specificity of 72.2%, and an area under ROC curve (AUC) of 0.860. Moreover, both Cho/NAA and Cho/Cr in the AQoCE approach show a significant difference (p≤0.019) between tumoral, peritumoral, and contralateral areas. The comparison between the results of AQoCE and Siemens MRS processing software are also discussed in this paper.

Conclusions

The AQoCE approach is an automated method of residual water removal and metabolite quantification. It can be applied to multi-voxel ¹H-MRS for evaluating brain glioma grading and demonstrating characteristics of brain glioma metabolism. It can also detect infiltration in the peritumoral area. Under the limited clinical data used, AQoCE is significantly more versatile and efficient compared to the reference approach of Siemens.

Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy

CONTEXT

With the advent of new imaging modalities, radiologists are faced with handling increasing volumes of data for diagnosis and treatment planning. The use of automated and intelligent systems is becoming essential in such a scenario. Machine learning, a branch of artificial intelligence, is increasingly being used in medical image analysis applications such as image segmentation, registration and computer-aided diagnosis and detection. Histopathological analysis is currently the gold standard for classification of brain tumors. The use of machine learning algorithms along with extraction of relevant features from magnetic resonance imaging (MRI) holds promise of replacing conventional invasive methods of tumor classification.

AIMS

The aim of the study is to classify gliomas into benign and malignant types using MRI data.

SETTINGS AND DESIGN

Retrospective data from 28 patients who were diagnosed with glioma were used for the analysis. WHO Grade II (low-grade astrocytoma) was classified as benign while Grade III (anaplastic astrocytoma) and Grade IV (glioblastoma multiforme) were classified as malignant.

METHODS AND MATERIALS

Features were extracted from MR spectroscopy. The classification was done using four machine learning algorithms: multilayer perceptrons, support vector machine, random forest and locally weighted learning.

RESULTS

Three of the four machine learning algorithms gave an area under ROC curve in excess of 0.80. Random forest gave the best performance in terms of AUC (0.911) while sensitivity was best for locally weighted learning (86.1%).

CONCLUSIONS

The performance of different machine learning algorithms in the classification of gliomas is promising. An even better performance may be expected by integrating features extracted from other MR sequences.

Evaluation of the diagnostic performance of magnetic resonance spectroscopy in brain tumors: a systematic review and meta-analysis

Object

The aim of this study was to determine the suitability of magnetic resonance spectroscopy (MRS) for screening brain tumors, based on a systematic review and meta-analysis of published data on the diagnostic performance of MRS.

Methods

The PubMed and PHMC databases were systematically searched for relevant studies up to December 2013. The sensitivities and specificities of MRS in individual studies were calculated and the pooled diagnostic accuracies, with 95% confidence intervals (CI), were assessed under a fixed-effects model.

Results

Twenty-four studies were included, comprising a total of 1013 participants. Overall, no heterogeneity of diagnostic effects was observed between studies. The pooled sensitivity and specificity of MRS were 80.05% (95% CI = 75.97%–83.59%) and 78.46% (95% CI: 73.40%–82.78%), respectively. The area under the summary receiver operating characteristic curve was 0.78. Stratified meta analysis showed higher sensitivity and specificity in child than adult. CSI had higher sensitivity and SV had higher specificity. Higher sensitivity and specificity were obtained in short TE value.

Conclusion

Although the qualities of the studies included in the meta-analysis were moderate, current evidence suggests that MRS may be a valuable adjunct to magnetic resonance imaging for diagnosing brain tumors, but requires selection of suitable technique and TE value.

Assessment of the intrinsic radiosensitivity of glioma cells and monitoring of metabolite ratio changes after irradiation by 14.7-T high-resolution ¹H MRS

Gliomas are the most common type of primary brain tumor. Radiation therapy (RT) is the primary adjuvant treatment to eliminate residual tumor tissue after surgery. However, the current RT guided by conventional imaging is unsatisfactory. A fundamental question is whether it is possible to further enhance the effectiveness and efficiency of RT based on individual radiosensitivity. In this research, to probe the correlation between radiosensitivity and the metabolite characteristics of glioma cells in vitro, a perchloric acid (PCA) extracting method was used to obtain water-soluble metabolites [such as N-acetylaspartate (NAA), choline (Cho), creatine (Cr) and succinate (Suc)]. Spectral patterns from these processed water-soluble metabolite samples were acquired by in vitro 14.7-T high-resolution ¹H MRS. Survival fraction analysis was performed to test the intrinsic radiosensitivity of glioma cell lines. Good ¹H MRS of PCA extracts from glioma cells was obtained. The radiosensitivity of glioma cells correlated positively with the Cho/Cr and Cho/NAA ratios, but negatively with the Suc/Cr ratio. Irradiation of the C6 cell line at different X-ray dosages led to changes in metabolite ratios and apoptotic rates. A plateau phase of metabolite ratio change and a decrease in apoptotic rate were found in the C6 cell line. We conclude that in vitro high-resolution ¹H MRS possesses the sensitivity required to detect subtle biochemical changes at the cellular level. ¹H MRS may aid in the assessment of the individual radiosensitivity of brain tumors, which is pivotal in the identification of the biological target volume.

Impacts of MR spectroscopic imaging on glioma patient management

Magnetic resonance (MR) modalities are routine imaging tools in the diagnosis and management of gliomas. MR spectroscopic imaging (MRSI), which relies on the metabolic characteristics of tissues, has been developed to accelerate the understanding of gliomas and to aid in effective clinical decision making and development of targeted therapies. In this review, the potentials and practical challenges to frequently use this technique in clinical management of gliomas are discussed. The applications of new biomarkers detectable by MRSI in differential glioma diagnosis, pre- and post-treatment evaluations, and neurosurgery are also addressed.

Spectroscopic evaluation of glioma grading at 3T: the combined role of short and long TE

Purpose. To evaluate the diagnostic value of 3T ¹H-MRS in grading cerebral gliomas using short and long echo times. Methods. 1H-MRS was performed on 71 patients with untreated cerebral gliomas. Metabolite ratios of NAA/Cr, Cho/Cr, Cho/NAA, and mI/Cr were calculated for short and long TE and compared between low and high grade gliomas. Lipids were qualitatively evaluated. ROC analysis was performed to obtain the cut-off values for the metabolic ratios presenting statistical difference between the two glioma grades. Results. Intratumoral Cho/Cr at both TEs and long TE Cho/NAA were significantly different between low and high grade gliomas. Peritumoral NAA/Cr of both TEs, as well as long TE Cho/Cr and Cho/NAA ratios, significantly differentiated the two tumor grades. Diagnostic sensitivity of peritumoral short TE NAA/Cr proved to be superior over the other metabolic ratios, whereas intratumoral short TE Cho/Cr reached the highest levels of specificity and accuracy. Overall, short TE 1H-MRS reached higher total sensitivity in predicting glioma grade, over long TE. Conclusion. An advantage was found in using short TE over long TE 1H-MRS in the discrimination of low versus high grade gliomas. Moreover, the results suggested that the peritumoral area of gliomas may be more valuable in predicting glioma grade than using only the intratumoral area.

Proton MR spectroscopy of central neurocytoma using short and long echo time: new proofs for the existence of glycine and glutamate

RATIONALE AND OBJECTIVES

Central neurocytomas (CNCs) are rare benign tumors typically located in the lateral ventricle of the central nervous system. The authors report five patients with CNCs and review 16 previously published studies that included 52 patients with CNCs to explore the magnetic resonance spectroscopic features of CNCs.

MATERIALS AND METHODS

Five patients with CNCs were retrospectively reviewed. They were examined using point-resolved spectroscopic series with short and/or long echo times. The integrals of choline, creatine, and the 3.55-ppm peak were determined using Magnetic Resonance User Interface software, and the metabolite ratios relative to creatine were obtained. In two cases, T2 relaxation times of choline and the metabolite resonance at 3.55 ppm were calculated using data points acquired with different echo times and an exponential decay model.

RESULTS

Consistent with previously published studies, all five patients showed highly increased choline and reduced N-acetylaspartate and creatine. Four patients in the present study and 35 in published data demonstrated prominent peaks at 3.55 ppm, which were assigned to glycine because of its relaxation pattern and long T2 relaxation time. In addition, increased in vivo glutamate and glutamine was also confirmed in three patients examined with short echo times. Alanine and lactate peaks were observed in three and two patients, respectively.

CONCLUSIONS

The present study shows that the 3.55-ppm peak characteristic of CNC should be assigned to glycine according to its T2 relaxation time. Besides increased glycine and choline, the presence of glutamate or glutamine, which appears on series with short echo times, may further confirm the diagnosis of CNC.

The use of neuroimaging to guide the histologic diagnosis of central nervous system lesions

Recent advances in neuroimaging techniques, particularly in magnetic resonance imaging, have led to substantially improved spatial anatomic resolution such that subtle or small central nervous system lesions, which could go undetected on gross examination of brain sections, are now readily identified on imaging. Although neuroimaging is generally considered the surrogate of gross neuropathology, it is still not a substitute for tissue diagnosis. Rather, it can be a valuable tool for the surgical pathologist in the process of formulating a differential diagnosis based on location and imaging features, as well as in identifying radiologic/pathologic discordance, such as the possible undersampling of a heterogenous glioma, which could lead to underestimation of the tumor grade. The following review focuses on the application of neuroimaging techniques, mainly magnetic resonance imaging, to the histologic diagnosis of central nervous system lesions, and the correlation of imaging features of infiltrative gliomas with histologic findings pertinent to tumor grading. The use of advanced functional magnetic resonance methods, specifically diffusion-weighted imaging, perfusion-weighted imaging, and magnetic resonance spectroscopy is also discussed, as well as the common pitfalls in imaging interpretation.

Choline metabolism in malignant transformation

Abnormal choline metabolism is emerging as a metabolic hallmark that is associated with oncogenesis and tumour progression. Following transformation, the modulation of enzymes that control anabolic and catabolic pathways causes increased levels of choline-containing precursors and breakdown products of membrane phospholipids. These increased levels are associated with proliferation, and recent studies emphasize the complex reciprocal interactions between oncogenic signalling and choline metabolism. Because choline-containing compounds are detected by non-invasive magnetic resonance spectroscopy (MRS), increased levels of these compounds provide a non-invasive biomarker of transformation, staging and response to therapy. Furthermore, enzymes of choline metabolism, such as choline kinase, present novel targets for image-guided cancer therapy.

Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction

BACKGROUND

A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking.

PURPOSE

To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients.

MATERIAL AND METHODS

T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression.

RESULTS

Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC = 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001).

CONCLUSION

Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients.